Issues »  Volume 48, Issue 6

Features of the Motion of the Critical Segment of Dislocation in a Multicomponent Alloy

M. I. Lugovy$^{1}$, D. G. Verbylo$^{1}$, М. P. Brodnikovskyy$^{1}$, T. I. Verbytska$^{2}$, D. S. Leonov$^{3}$, M. Yu. Barabash$^{2,3,4}$

$^{1}$I. M. Frantsevych Institute for Problems in Materials Science, N.A.S. of Ukraine, 3 Omeljan Pritsak Str., UA-03142 Kyiv, Ukraine
$^{2}$National Technical University of Ukraine ‘Igor Sikorsky Kyiv Polytechnic Institute’, 37 Beresteiskyi Ave., UA-03056 Kyiv, Ukraine
$^{3}$Technical Centre, N.A.S. of Ukraine, 13 Pokrovs’ka Str., UA-04070 Kyiv, Ukraine
$^{4}$Institute for Applied Control Systems, N.A.S. of Ukraine, 42 Academician Hlushkov Ave., UA-03187 Kyiv, Ukraine

Received: 26.02.2026; final version - 13.03.2026. Download: PDF

The motion of a critical segment of a dislocation in a field of stochastic shear stresses within the glide plane in a multicomponent alloy can be considered as one-dimensional motion of an effective point object to analyse thermal activation. However, such point objects should be regarded as under the influence of an effective one-dimensional distribution of shear stresses, the characteristics of which differ from the characteristics of a real two-dimensional distribution. A method for determining the characteristics of an effective distribution is proposed. Such distribution can be found by averaging the field of stochastic shear stresses over a characteristic region of the glide plane, which is a rectangle with dimensions equal to the length and height of the average bulge of the critical segment. It is possible because moving critical segments can be considered as ‘smeared’ ones over this characteristic region. Thus, the standard deviation and correlation length of an effective distribution can be determined from the known two-dimensional distribution. With the use of computer simulation, the dependence of the characteristics of the one-dimensional distribution on the characteristic averaging length is determined. As shown, the standard deviation of an effective distribution decreases and its correlation length increases with increasing averaging length, i.e., the height of the average bulge. Therefore, the effective distribution has a smaller standard deviation and a longer correlation length compared to the corresponding characteristics of the field of stochastic shear stresses. The estimation of characteristics of effective distribution of shear stresses is important to analyse dislocation motion assisted with thermal activation in a multicomponent alloy.

Key words: multicomponent alloy, dislocation, shear stress, standard deviation, correlation length.

URL: https://mfint.imp.kiev.ua/en/abstract/v48/i06/0569.html

DOI: https://doi.org/10.15407/mfint.48.06.0569

PACS: 46.35.+z, 61.72.Bb, 61.72.Hh, 61.72.Lk, 62.20.fg, 83.10.Ff

Citation: M. I. Lugovy, D. G. Verbylo, М. P. Brodnikovskyy, T. I. Verbytska, D. S. Leonov, and M. Yu. Barabash, Features of the Motion of the Critical Segment of Dislocation in a Multicomponent Alloy, Metallofiz. Noveishie Tekhnol., 48, No. 6: 569–586 (2026)

REFERENCES
  1. D. B. Miracle and O. N. Senkov, Acta Mater., 122: 448 (2017).
  2. E. P. George, W. A. Curtin, and C. C. Tasan, Acta Mater., 188: 435 (2020).
  3. R. Labusch, Czech. J. Phys. B, 31: 165 (1981).
  4. L. A. Gypen and A. Deruyttere, J. Mater. Sci., 12, Iss. 5: 1028 (1977).
  5. F. Otto, A. Dlouhy, Ch. Somsen, H. Bei, G. Eggeler, and E. P. George, Acta Mater., 61: 5743 (2013).
  6. A. Gali and E. P. George, Intermetallics, 39: 74 (2013).
  7. S. J. Sun, Y. Z. Tian, H. R. Lin, X. G. Dong, Y. H. Wang, Z. J. Wang, and Z. F. Zhang, J. Alloys Compd., 806: 992 (2019).
  8. A. V. Podolskiy, E. D. Tabachnikova, V. V. Voloschuk, V. F. Gorban, N. A. Krapivka, and S. A. Firstov, Mater. Sci. Eng. A, 710: 136 (2018).
  9. S. O. Firstov, T. G. Rogul, N. A. Krapivka, and S. I. Chugunova, Metallofiz. Noveishie Tekhnol., 40, No. 2: 219 (2018) (in Russian).
  10. S. O. Firstov and T. G. Rogul, Metallofiz. Noveishie Tekhnol., 39, No. 1: 33 (2017) (in Russian).
  11. M. Zaiser, Phil. Mag. A, 82, Iss. 15: 2869 (2002).
  12. J.-H. Zhai and M. Zaiser, Mater. Sci. Eng. A, 740–741: 285 (2019).
  13. G. Leyson, W. Curtin, L. Hector, and C. F. Woodward, Nature Mater., 9: 750 (2010).
  14. G. P. M. Leyson, W. A. Curtin, L. G. Hector Jr., and Ch. F. Woodward, Acta Mater., 60: 3873 (2012).
  15. G. P. M. Leyson and W. A. Curtin, Modelling Simulation Mater. Sci. Eng., 24: 065005 (2016).
  16. C. Varvenne, A. Luque, and W. A. Curtin, Acta Mater., 118: 164 (2016).
  17. C. Varvenne, G. P. M. Leyson, M. Ghazisaeidi, and W. A. Curtin, Acta Mater., 124: 660 (2017).
  18. G. Laplanche, J. Bonneville, C. Varvenne, W. A. Curtin, and E. P. George, Acta Mater., 143: 257 (2018).
  19. W. G. Nöhring and W. A. Curtin, Scripta Mater., 168: 119 (2019).
  20. G. Bracq, M. Laurent-Brocq, C. Varvenne, L. Perrière, W. A. Curtin, J.-M. Joubert, and I. Guillot, Acta Mater., 177: 266 (2019).
  21. Y. Hu, B. A. Szajewski, D. Rodney, and W. A. Curtin, Modelling Simulation Mater. Sci. Eng., 28: 015005 (2020).
  22. G. Péterffy, P. D. Ispánovity, M. E. Foster, X. Zhou, and R. B. Sills, Mater. Theory, 4: 6 (2020).
  23. R. Pasianot and D. Farkas, Computational Mater. Sci., 173: 109366 (2020).
  24. J. D. Eshelby, Solid State Physics, 3: 79 (1956).
  25. R. L. Fleischer, Acta Metallurgica, 11: 203 (1963).
  26. I. Toda-Caraballo, Scripta Mater., 127: 113 (2017).
  27. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 3: 24 (2021) (in Ukrainian).
  28. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 4–5: 12 (2022) (in Ukrainian).
  29. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 7: 3 (2023) (in Ukrainian).
  30. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 6: 15 (2023) (in Ukrainian).
  31. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Metallofiz. Noveishie Tekhnol., 47, No. 3: 303 (2025).
  32. M. Lugovy, V. Slyunyayev, and M. Brodnikovskyy, Prog. Natural Sci. Mater. Int., 31: 95 (2021).
  33. M. Lugovy, V. Slyunyayev, M. Brodnikovskyy, and S. O. Firstov, Elektronnaya Mikroskopiya i Prochnost’ Materialov, 23: 3 (2017) (in Ukrainian).
  34. M. Lugovy, V. Slyunyayev, and M. Brodnikovskyy, Elektronnaya Mikroskopiya i Prochnost’ Materialov, 25: 26 (2019) (in Russian).
  35. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 2: 19 (2021) (in Ukrainian).
  36. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 4/5: 36 (2022) (in Ukrainian).
  37. S. O. Firstov and T. G. Rogul, Metallofiz. Noveishie Tekhnol., 44, No. 1: 127 (2022) (in Ukrainian).
  38. M. I. Lugovy, D. G. Verbylo, and M. P. Brodnikovskyy, Uspikhy Materialoznavstva, 8–9: 13 (2024) (in Ukrainian).
  39. A. S. Argon, Strengthening Mechanisms in Crystal Plasticity (Oxford: Oxford University Press: 2008).
  40. U. F. Kocks, A. S. Argon, and M. F. Ashby, Prog. Mater. Sci., 19: 110 (1975).
  41. F. R. N. Nabarro, The Physics of Metals (Ed. P. B. Hirsch) (Cambridge: Cambridge University Press: 1976), p. 152.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License
© 1979 “G. V. Kurdyumov Institute for Metal Physics of the N.A.S. of Ukraine”